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22 results for “Wave scattering”
Dataset: Mapping intrinsic and scattering attenuation in the southern Aegean crust using S-wave envelope inversion and sensitivity kernels derived from perturbation theory
<p><strong>Data Set S1: </strong>File “ds01.csv” contains the catalogue of relocated events used in this study. The columns in the file represent origin time (in year-month-day’H’hour’M’minute’S’seconds format), event longitude, event latitude, event depth in a sequential manner.</p> <p><strong>Data Set S2: </strong>File “ds02.zip” contains four ASCII data files (ray_prmtrs12.txt, ray_prmtrs24.txt, ray_prmtrs48.txt and ray_prmtrs816.txt). The data files contain scattering coefficient (<em>g<sup>*</sup></em>) and intrinsic coefficient (<em>b</em>) values in 1-2, 2-4 Hz, 4-8 Hz and 8-16 Hz bands respectively. The columns in the text files represent event latitude, event longitude, event depth, station latitude, station longitude, station velocity, envelope duration, <em>g<sup>*</sup></em>, <em>b</em>, early-S window length, percentage error in early-S window, percentage error for full envelope, and event origin time in a sequential manner.</p> <p><strong>Data Set S3: </strong>File “ds03.zip” contains four data files (envnodes15g_3_3_1-2.txt, envnodes15g_3_3_2-4.txt, envnodes15g_3_3_4-8.txt, and envnodes15g_3_3_8-16.txt), one BASH script containing GMT and Octave commands (Qs_envg.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of log<sub>10</sub>(<em>Q<sub>sc</sub></em><sup>-1</sup>) using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above.</p> <p><strong>Data Set S4: </strong>File “ds04.zip” contains four data files (envnodes15b_3_3_1-2.txt, envnodes15b_3_3_2-4.txt, envnodes15b_3_3_4-8.txt, and envnodes15b_3_3_8-16.txt), one BASH script containing GMT and Octave commands (Qi_env.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of log<sub>10</sub>(<em>Q<sub>i</sub></em><sup>-1</sup>) using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above.</p> <p><strong>Data Set S5: </strong>File “ds05.zip” contains four data files (envnodes15a_3_3_1-2.txt, envnodes15a_3_3_2-4.txt, envnodes15a_3_3_4-8.txt, and envnodes15a_3_3_8-16.txt), one BASH script containing GMT and Octave commands (albd_env.gmt), and a lat-long coordinate file (SAegean_poly_coord_extnd.txt) to mask the area outside the seismic network. The data files contain Albedo (<em>B<sub>o</sub></em>) as % values in 1-2, 2-4, 4-8 and 8-16 Hz bands respectively. The columns in the text files represent node latitude, node longitude and <em>B<sub>o</sub></em> value of the node sequentially. This GMT script also uses GSHHG coastline data whose path can be added to the script by changing the value of variable GDIR at the beginning of the script. The BASH script file can be run to see the spatial distribution of <em>B<sub>o</sub></em> using GMT-6 (Wessel et al., 2019) and Octave version 5.1 and above. </p>
Using thin films of phase-change material for active tuning of terahertz waves scattering on dielectric cylinders
<p>The uploaded files contain the data generated by MATLAB and used to plot a part of the figures, and a sample code.</p> <p>Research supported by Narodowe Centrum Nauki, project no UMO-2020/39/I/ST3/02413.</p>
Dataset: scattering of acoustic waves by vortices
<p>This dataset contains the data associated with the following paper: V. Clair & G. Gabard, Spectral broadening of acoustics waves by convected vortices, <em>Journal of Fluid Mechanics</em>, 841, pp. 50-80, 2018.</p>
Dataset for: In-operando microwave scattering-parameter calibrated measurement of a Josephson travelling wave parametric amplifier
<p>Dataset for manuscript "In-operando microwave scattering-parameter calibrated measurement of a Josephson travelling wave parametric amplifier", <a href="https://arxiv.org/abs/2406.03063">arXiv:2406.03063</a></p> <p>Containing the uncalibrated raw measurement data and the calibrated dataset after applying the 8-term error model.</p>
Relativistic Electron Precipitation Events (driven by waves or field line scattering) from POES 2-second data
<p>This repository contains the list of relativistic electron precipitation from POES data since 2012.</p> <p>Please refer to the read_me file for further details.</p> <p> </p> <p><strong>You are free to use this for your research. However, before doing so, please contact Luisa Capannolo at luisacap@bu.edu.</strong></p> <p> </p> <p>This dataset is associated with the paper under review titled "Properties of Relativistic Electron Precipitation: A Comparative Analysis of Wave-Induced and Field Line Curvature Scattering Processes" by Capannolo, Staff, Li, Duderstadt, Sivadas, Petitt, Elliot, Qin, Shen, and Ma.</p>
Calculation data for "Scattering of Radiation Belt Electrons by Fast Magnetosonic Waves: Considering the Kinetic Effects"
<p>Here are the calculation data for "Scattering of Radiation Belt Electrons by Fast Magnetosonic Waves: Considering the Kinetic Effects", using the format of ".mat". </p> <p>Term of "cold_plasma_dispersion_relation.mat" is the numerical results of cold plasma dispersion relation for MS waves;</p> <p>Term of "kinetic_dispersion_relation.mat" is the numerical results of kinetic dispersion relation for MS waves, using the WHAMP code by K. Rönnmark;</p> <p>Term of "Diffusion_coefficients_cold.mat" is the diffusion rates calculated based on the cold plasma dispersion relation;</p> <p>Term of "Diffusion_coefficients_kinetic.mat" is the diffusion rates calculated based on the kinetic dispersion relation;</p> <p>To be noted, the "D_{\alpha\alpha}_Bw2" in term "Diffusion_coefficients_kinetic.mat" is derived from the inferred wave magnetic field power spectral density.</p>
Nonlinear scattering of 90-degree pitch angle electrons in the outer radiation belt by large-amplitude EMIC waves
<p>This file is a collection of numeric data files which were used to create all figures in the paper (under review as of December 19, 2019). All the data were obtained from numerically solving the Lorentz equation of motion for 5 MeV electrons under EMIC waves superposed onto a dipolar background magnetic field. </p>
Radiative and climatic impacts of coarse aerosols scattering in the long-wave spectrum
<p>The data deposited on the site concern the output of the ARPEGE climate model at monthly resolution. This concerns the different variables used and analysed in the article. They include simulations with LW aerosol scattering (LWAS) and without aerosol scattering (NOLWAS). The data description, resolution and information on fields outputs are available in each NetCDF file submitted.</p>
Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering
<p>The repository contains the data presented in the figures in the manuscript entitled <br> "Spin wave stiffness and damping in a frustrated chiral helimagnet Co8Zn8Mn4 as measured by small-angle neutron scattering".</p> <p>Requests for further information can be directed to the corresponding authors Victor Ukleev (victor.ukleev 'at' psi.ch).</p>
Data and plotting code for "Energetic electron scattering by kinetic Alfvén waves at strong magnetic field gradients of dipolarization front"
<p>This publication includes the dataset and plotting code for reproducing results and figures of the manuscript "Energetic electron scattering by kinetic Alfvén waves at strong magnetic field gradients of dipolarization front", which was submitted to Physics of Plasma for potential publication. In this paper, we use test particle simulations to study energetic electron pitch angle and momentum scattering driven by kinetic Alfvén waves, at the magnetic field gradients associated with the dipolarization front, current sheet and plasma sheet fields in the magnetotail. </p> <p>The simulation data contains time history of 1000 test particle trajectories, momentum, energy, and KAW wave phases recorded every 0.001 second. Each simulation for different electron energies and pitch angles has a size of over 1 GB, so here we have only included one example of test particle simulation run associated with Figure 3. Only the final results of pitch angle diffusion coefficients are provided associated with Figure 4. A full set of time history results of all test particle simulation runs for Figure 4 will be available upon reasonable request (yshen@epss.ucla.edu). </p> <p>Detailed descriptions:</p> <p> PoP_figure_1.m --- Matlab plotting code for reproducing magnetic field model and geometry for Figure 1.</p> <p> PoP_figure_2.m --- Matlab plotting code for reproducing resonant energy as a function of wave normal angle, electron pitch angle, and field model parameters in Figure 2.</p> <p> PoP_figure_3.m --- Reading test particle simulation data and plotting code for reproducing Figure 3. Please ensure proper directory setting to read test particle data files. </p> <p> PoP_figure_4_5.m --- Reading saved bounce-averaged diffusion coefficient data and plotting Figure 4 and Figure 5.</p> <p> Daa_Energy_alpha_ad3xp15_e1.csv --- Electron diffusion coefficients driven by KAW scattering as a function of energy and pitch angle obtained from test particle simulations. KAW wave amplitude is set to 1 mV/m. Electrons are initiated from a position of x=150 km within the dipolarization front.</p> <p> Tau_Energy_alpha_xp15.csv --- Electron bounce periods as a function of energy and pitch angle based on numerical test particle simulations without KAW input.</p> <p> pKAW_1000p_dify_E100keV_PA5_Daa_E4_pop.zip --- Data files containing 1000 test particle trajectories, momentum and adiabatic invariant. This one single run is for electrons with an energy of 100 keV and a pitch angle of 5 degree, under influence of KAW wave electric field of 4 mV/m. This dataset is used to plot Figure 3. </p> <p> pKAW_1000p_dify_init_Ppara_mue_E100_PA4_Daa_E4_pop.dat --- initial parallel momentum and first adiabatic invariant of 1000 test particles. Read this file for plotting Figure 3. </p> <p> Bxyz.m --- calculate model magnetic field for given positions in x, y, and z</p> <p> FAC.m --- convert local x, y, z coordinates to field-aligned coordinates</p> <p> gradB.m --- calculate the gradient of magnetic field for given positions in x, y, and z</p> <p> E_to_pnorm_hsr.m --- calculate normalized momentum based on relativistic electron energy</p> <p> mysubplot.m --- plotting function to replace subplot routine of Matlab</p> <p> </p> <p> </p>
Separation of Intrinsic and Scattering Seismic Wave Attenuation in the Crust of Central and South-Central Alaska
<p>This dataset provides essential support for understanding the study and includes all necessary files for anyone wishing to reproduce any of the results</p>
Resonant Scattering of Sub-keV Electrons by Beam-driven Electron Cyclotron Harmonic Waves
<p>Data repository for ``Resonant Scattering of Sub-keV Electrons by Beam-driven Electron Cyclotron Harmonic Waves''. This repository contains raytracing results of beam-driven ECH waves and loss-cone-driven ECH waves calculated from HOTRAY ray-tracing program.</p>
Direct evidence of the pitch angle scattering of relativistic electrons induced by EMIC waves
<p>High rate MagEIS data for the submitted paper "Direct evidence of the pitch angle scattering of relativistic electrons induced by EMIC waves"</p>
Supplement to "Microwave and submillimeter wave scattering of oriented ice particles"
<p>This data set contains the simulated brightness temperatures and the corresponding atmospheric states for the radiative transfer simulations for the journal article "<a href="https://doi.org/10.5194/amt-2019-382">Microwave and submillimeter wave scattering of oriented ice particles</a>", which is on Atmospheric Measurement Techniques (AMTD).</p>
Data and code for the publication 'Fully Non-Linear Neuromorphic Computing with Linear Wave Scattering'
<p>This repository contains the source code for the paper <a href="https://arxiv.org/abs/2308.16181" rel="nofollow">https://arxiv.org/abs/2308.16181</a> on nonlinear neuromorphic computing via linear wave scattering as well as the source data for the figures in the paper.</p> <p>The idea behind this work is to send optical waves through a linear scattering system like an array of waveguides and optical resonators. These optical resonators or other elements may have tuneable parameters. These tuneable parameters now serve two functions in trying to use the system to solve a machine-learning task: Some of the parameters can be used to inject the input (e.g. images to be classified). Other parameters are trainable and will be slowly updated during training. The code given here simulates physical scattering setups, observes the scattering response for many different training samples, and updates the trainable parameters via gradient descent to minimize the deviation from the desired target output for the training samples. Evaluation of the scattering response as well as calculation of the gradients is done using jax, and training updates are implemented via jax or optax.</p> <p>See the two subdirectories for the code used in handwritten-digit recognition (a scaled-down version of MNIST) and for fashion-MNIST (with many more neurons and trainable parameters). This code can be run directly to reproduce the results shown in the figures (although a GPU is advisable). To run the code, you need to install jax and optax (and tensorflow for importing data sets).</p>
Raw data and code for: Shaping entangled photons through thick scattering media using an advanced wave beacon
<p>The paper is here: </p> <p>https://arxiv.org/abs/2403.18324</p> <p>And available as a reposity also on bitbucket: </p> <p>https://bitbucket.org/rshekel/klyshko-optimization-data/src/master/</p>
Differences in Scattering Properties of the Shallow Crusts of Earth, Mars, and the Moon Revealed by P-Wave Receiver Functions - Dataset
<p>This version includes three parts. The first part is the seismic data set of Earthquakes, Marsquakes, and Moonquakes used in "Differences in Scattering Properties of the Shallow Crusts of Earth, Mars, and the Moon Revealed by P-Wave Receiver Functions" by Shi et al. (2023). In the data set of Earthquakes and Marsquakes, the direct P wave starts after 120 s. In the data set of Moonquakes, the direct P wave starts after 50 s. The second part is the velocity models used in the article for the Earth, Mars, and Moon. The third part is the code used to reproduce all the figures in the main text.</p>
Nonresonant scattering of energetic electrons by electromagnetic ion cyclotron waves: spacecraft observations and theoretical framework
<p>This repository contains the simulation dataset, plotting scripts, and optimization package for the manuscript ``Nonresonant scattering of energetic electrons by electromagnetic ion cyclotron waves: spacecraft observations and theoretical framework''.</p> <p>*.h5 are snapshots of EMIC wave field (By and Bz) from deltaf-PIC simulations.</p> <p>test_particle.zip contains the test particle data in the wave field of deltaf-PIC simulations.</p> <p>*.py are plotting scripts to visualize the wave field, test particle simulation results, and theoretical predictions.</p> <p>optimization.zip contains the main subroutines for optimization of wave power spectrum to produce the measured electron precipitation.</p> <p>plt_style.txt is an auxillary style file for matplotlib plot.</p> <p> </p>
A Brillouin light scattering study of the spin-wave magnetic field dependence in a magnetic hybrid system made of an artificial spin-ice structure and a film underlayer
<p>We present a combined Brillouin light scattering (BLS) and micromagnetic simulation investigation of the magnetic-field-dependent<br> spin-wave spectra in a hybrid structure made of permalloy (NiFe) artificial spin-ice (ASI) systems, composed of stadium-shaped nanoislands, deposited on the top of an unpatterned permalloy film with a nonmagnetic spacer layer. The thermal spin-wave spectra were recorded by BLS as a function of the magnetic field applied along the symmetry direction of the ASI sample. Magneto-optic Kerr effect magnetometry was used to measure the hysteresis loops in the same orientation as the BLS measurements. The frequency and the intensity of several spin-wave modes detected by BLS were measured as a function of the applied magnetic field. Micromagnetic simulations enabled us to identify the modes in terms of their frequency and spatial symmetry and to extract information about the existence and strength of the dynamic coupling, relevant only to a few modes of a given hybrid system. Using this approach, we suggest a way to understand if the dynamic coupling between ASI and film modes is present or not, with interesting implications for the development of future three-dimensional magnonic applications and devices.</p>
Passive seismic imaging of near vertical structures around the SAFOD site, California, jointly using scattered P and SH waves
<p>1, The P and S velocity model are in the velocity folder which written by binary format (float). The size of the velocity model is 101*101*56(Nx Ny Nz) with a 200 meter grid. The upleft corner is (-10km -10km -1km). The unit of the velocity is km/s.</p> <p>2, The stations and events are in the geometry folder:</p> <p>the format of the file is</p> <p>Number of the stations/events</p> <p>Name of the stations/events, X(km), Y(km), Z(km). </p> <p>the origin of the coordinates system is the bole hole SAFOD, and the local coordinates was rotated by 40.5 degree.</p> <p>The name of the events was the origin time (precise to the minute) of the events.</p> <p>For example:</p> <p>the 1227042400 indicates that </p> <p>Year JulianDay hour minute second</p> <p>2001 227 04 24 00</p> <p>You can get the details and download the waveform at the website https://www.fdsn.org/networks/detail/XN_2000/ and https://www.fdsn.org/networks/detail/BP/</p> <p>2.1) the "events_3.7km_56" includes 56 events that was at the same depth~3.7km, The common station (The TANK Station) gather was shown in figure 6. </p> <p>2.2) "events_all" indicates 560 events that shown in Figure 4, and there are about 10 events not in the SAF, we did not use them, the "events_rm_outlier" are the 546 events we lastly used.</p> <p>2.3) "stations.dat.65" is the combination of the PASO and HRSN that in 20km square area as shown in Figure1.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.